[CI] Add E2E Blackwell Quantized MoE Test

[mgoin]

Purpose

Adds a new "Blackwell Quantized MoE Test" job that is solely meant to run critical MoE models (Llama 4, Qwen, DeepSeek, GPT-OSS) that we have many ways of running on Blackwell, through various quantization backends.
It loads the model with dummy weights and for just a few layers to make sure we can pass process_weights_after_loading, torch.compile, cudagraph capture, and serve a request.

Test Plan

Test Result

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• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
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[chatgpt-codex-connector]

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[gemini-code-assist]

Code Review

This pull request introduces end-to-end tests for quantized Mixture-of-Experts (MoE) models on Blackwell GPUs, which is a valuable addition for ensuring hardware-specific features work correctly.

My review identified two main issues:

1. A critical issue in the CI configuration (.buildkite/test-pipeline.yaml) where the new test job has an incomplete and partially incorrect list of file dependencies. This could prevent the test from running when relevant code, including the test file itself, is modified.
2. A high-severity issue in the new test file (tests/quantization/test_blackwell_moe.py) where the GPU capability check should be more flexible to allow running on future GPU architectures.

I have provided specific suggestions to address these points. Overall, the changes are a good step towards validating vLLM on new hardware, and with these fixes, the CI setup and tests will be more robust.

[yewentao256]

Thanks for the work!

[yewentao256]

LGTM, thanks for the work!